Scalable Vector Search in Postgres

Scalable Vector Search in Postgres

Scalable Vector Search in Postgres

PGVecto.rs is a Postgres extension that enables scalable vector search, allowing you to build powerful similarity-based applications on top of your Postgres database.

PGVecto.rs is a Postgres extension that enables scalable vector search, allowing you to build powerful similarity-based applications on top of your Postgres database.

PGVecto.rs is a Postgres extension that enables scalable vector search, allowing you to build powerful similarity-based applications on top of your Postgres database.

QUICK START

Build AI Applications at Scale

Build AI Applications at Scale

-- create table with a vector column
CREATE TABLE items (
  id bigserial PRIMARY KEY,
  embedding vector(3) NOT NULL -- 3 dimensions
);

-- insert values
INSERT INTO items (embedding)
VALUES ('[1,2,3]'), ('[4,5,6]');

-- create index
CREATE INDEX ON items USING vectors (embedding vector_l2_ops);

-- query the similar embeddings
SELECT * FROM items ORDER BY embedding <-> '[3,2,1]' LIMIT 5

Product Features

Revolutionize Vector Search, not Database.

Revolutionize Vector Search, not Database.

Better Filtering

Apply any filter conditions and join with other tables, achieving high recall and low latency, a distinctive edge over other vector databases.

Better Filtering

Apply any filter conditions and join with other tables, achieving high recall and low latency, a distinctive edge over other vector databases.

Better Filtering

Apply any filter conditions and join with other tables, achieving high recall and low latency, a distinctive edge over other vector databases.

Extended Vector Length

PGVecto.rs supports vector length up to 65535, suitable for the latest models.

Extended Vector Length

PGVecto.rs supports vector length up to 65535, suitable for the latest models.

Extended Vector Length

PGVecto.rs supports vector length up to 65535, suitable for the latest models.

Binary Vector Search

By utilizing adaptive retrieval techniques, binary vectors can maintain a high level of accuracy while significantly reducing memory usage by 30 times.

Binary Vector Search

By utilizing adaptive retrieval techniques, binary vectors can maintain a high level of accuracy while significantly reducing memory usage by 30 times.

Binary Vector Search

By utilizing adaptive retrieval techniques, binary vectors can maintain a high level of accuracy while significantly reducing memory usage by 30 times.

Hybrid Search

Leverage the full-text search functionality in PostgreSQL with pgvecto.rs to search text and vector data within a single query.

Hybrid Search

Leverage the full-text search functionality in PostgreSQL with pgvecto.rs to search text and vector data within a single query.

Hybrid Search

Leverage the full-text search functionality in PostgreSQL with pgvecto.rs to search text and vector data within a single query.

Faster, and Faster

4x faster than other postgres-based solutions.

Faster, and Faster

4x faster than other postgres-based solutions.

Faster, and Faster

4x faster than other postgres-based solutions.

Complete SQL Support

Full SQL support, enabling joins and filters without limitations or extra configuration.

Complete SQL Support

Full SQL support, enabling joins and filters without limitations or extra configuration.

Complete SQL Support

Full SQL support, enabling joins and filters without limitations or extra configuration.

USER TESTIMONIALS

Showcase with PGVecto.rs
Trusted by Many Open Source Projects

Showcase with PGVecto.rs
Trusted by Many Open Source Projects

© 2024 TensorChord Inc. All rights reserved.

© 2024 TensorChord Inc. All rights reserved.

© 2024 TensorChord Inc. All rights reserved.